LED Display System Characterisation Based on Wireless Communication Techniques: A Systematic Review
Isaac Collins Febaide,
Akpofure Enughwure
Issue:
Volume 11, Issue 2, June 2023
Pages:
21-26
Received:
12 January 2023
Accepted:
31 January 2023
Published:
6 July 2023
Abstract: The display of information and data in control and automation systems, campuses, hospitals and shopping malls have become seamless and attractive since the advent of LED display systems. There has been a need in determining the best options available in sending information or data to the LED display system putting different options into consideration. This paper reviews among many available options, wireless communications techniques that are employed in updating information on a LED display system by analyzing their characteristics in terms of cost, power consumption, transmission range, typical join time and user friendly graphical user interface in a bid to help readers choose which technique best suit their needs in design process based on the analyzed characteristics of these techniques. The LED display system Wireless communication techniques considered in this work are Bluetooth, WI-FI, Radio Frequency, GSM and IOT. IOT is shown to be the cheapest with ₦ 2700; radio frequency has a faster join time of 0.03 seconds; Bluetooth has the smallest maximum power consumption of 0.3 W with GSM and IOT having an infinite transmission range based on network availability. This paper will help researchers and designers choose wisely the best optimal option that best fits their design.
Abstract: The display of information and data in control and automation systems, campuses, hospitals and shopping malls have become seamless and attractive since the advent of LED display systems. There has been a need in determining the best options available in sending information or data to the LED display system putting different options into considerati...
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Towards a Bijective Co-simulation Model Between Physical and Virtual Environments, Adapted to a Platform for Autonomous Industrial Vehicles
Moïse Djoko-Kouam,
Alain-Jérôme Fougères
Issue:
Volume 11, Issue 2, June 2023
Pages:
27-44
Received:
31 May 2023
Accepted:
29 June 2023
Published:
11 July 2023
Abstract: One of the major challenges faced by Industry 4.0 is the use of Automated Guided Vehicles (AGVs) and, more broadly, autonomous mobile robots. While autonomy in road transportation vehicles can already be well characterized, it is a different story for autonomous vehicles used in industries, such as Autonomous Industrial Vehicles (AIVs). The implementation and deployment of AIV fleets in industrial sectors encounter various issues, including vehicle localization, employee acceptance, traffic flow, and the ability of vehicles to adapt to fluctuating and dynamic environments. The challenge that autonomous vehicles represent for the future of the digital industry is so significant that it makes sense from our vision to go through a step of joint physical and digital simulation of these vehicles and their environments. This step would assist industrials in their respective development and fine-tuning activities. The objective of this article is to demonstrate that all the elements available to us at present (research conducted in our laboratory, technological building blocks, operating scenarios already carried out, state of the art) logically allow us to project ourselves towards a Co-Simulation platform based on a bijective model between physical and virtual environments. Furthermore, this projection is enriched by the idea of a digital component of the platform, capable of taking into account in an agnostic way, the different possible forms of the physical part of this platform. Thus, simulation enables the consideration of constraints and requirements formulated by manufacturers and future users of autonomous vehicles. Our approach is progressive, as presented in this article, and it is based on experiments with Co-Simulation platforms that combine physical and virtual approaches. We provide a detailed description of our AIVs and their traffic environments. The static architecture of the platform is described using class diagrams. The dynamic behavior of the platform is described, thanks to sequence diagrams, state diagrams, and algorithmic flowcharts. We also propose an approach to estimate the position of AIVs based on the combination of matrix-based tagging with a section change management technique. As a result of the presented approach, all of these diagrams make it possible to document different operating scenarios of the Co-Simulation platform. Beyond these results, and to complement them before concluding, we describe several application cases related to both algorithmic position estimation metrology and electric battery characterization. This serves to illustrate the potential value of our Co-Simulation platform model.
Abstract: One of the major challenges faced by Industry 4.0 is the use of Automated Guided Vehicles (AGVs) and, more broadly, autonomous mobile robots. While autonomy in road transportation vehicles can already be well characterized, it is a different story for autonomous vehicles used in industries, such as Autonomous Industrial Vehicles (AIVs). The impleme...
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